01ca415721
Currently, computed hash keys are stored in a separate column family with respect to the MPT data they're generated from - this has several disadvantages: * A lot of space is wasted because the lookup key (`RootedVertexID`) is repeated in both tables - this is 30% of the `AriKey` content! * rocksdb must maintain in-memory bloom filters and LRU caches for said keys, doubling its "minimal efficient cache size" * An extra disk traversal must be made to check for existence of cached hash key * Doubles the amount of files on disk due to each column family being its own set of files Here, the two CFs are joined such that both key and data is stored in `AriVtx`. This means: * we save ~30% disk space on repeated lookup keys * we save ~2gb of memory overhead that can be used to cache data instead of indices * we can skip storing hash keys for MPT leaf nodes - these are trivial to compute and waste a lot of space - previously they had to present in the `AriKey` CF to avoid having to look in two tables on the happy path. * There is a small increase in write amplification because when a hash value is updated for a branch node, we must write both key and branch data - previously we would write only the key * There's a small shift in CPU usage - instead of performing lookups in the database, hashes for leaf nodes are (re)-computed on the fly * We can return to slightly smaller on-disk SST files since there's fewer of them, which should reduce disk traffic a bit Internally, there are also other advantages: * when clearing keys, we no longer have to store a zero hash in memory - instead, we deduce staleness of the cached key from the presence of an updated VertexRef - this saves ~1gb of mem overhead during import * hash key cache becomes dedicated to branch keys since leaf keys are no longer stored in memory, reducing churn * key computation is a lot faster thanks to the skipped second disk traversal - a key computation for mainnet can be completed in 11 hours instead of ~2 days (!) thanks to better cache usage and less read amplification - with additional improvements to the on-disk format, we can probably get rid of the initial full traversal method of seeding the key cache on first start after import All in all, this PR reduces the size of a mainnet database from 160gb to 110gb and the peak memory footprint during import by ~1-2gb. |
||
---|---|---|
.. | ||
aristo | ||
core_db | ||
era1_db | ||
kvt | ||
.gitignore | ||
README.md | ||
access_list.nim | ||
aristo.nim | ||
core_db.nim | ||
era1_db.nim | ||
kvstore_rocksdb.nim | ||
kvt.nim | ||
ledger.nim | ||
opts.nim | ||
storage_types.nim | ||
transient_storage.nim |
README.md
Nimbus-eth1 -- Ethereum execution layer database architecture
Last update: 2024-03-08
The following diagram gives a simplified view how components relate with regards to the data storage management.
An arrow between components a and b (as in a->b) is meant to be read as a relies directly on b, or a is served by b. For classifying the functional type of a component in the below diagram, the abstraction type is enclosed in brackets after the name of a component.
-
(application)
This is a group of software modules at the top level of the hierarchy. In the diagram below, the EVM is used as an example. Another application might be the RPC service. -
(API)
The API classification is used for a thin software layer hiding a set of different drivers where only one driver is active for the same API instance. It servers as sort of a logical switch. -
(concentrator)
The concentrator merges several sub-module instances and provides their collected services as a single unified instance. There is not much additional logic implemented besides what the sub-modules provide. -
(driver)
The driver instances are sort of the lower layer workhorses. The implement logic for solving a particular problem, providing a typically well defined service, etc. -
(engine)
This is a bottom level driver in the below diagram.+-------------------+ | EVM (application) | +-------------------+ | | v | +-----------------------------+ | | State DB (concentrator) | | +-----------------------------+ | | | | v | | +------------------------+ | | | Ledger (API) | | | +------------------------+ | | | | | | v | | | +--------------+ | | | | ledger cache | | | | | (driver) | | | | +--------------+ | | | | v | | | +----------------+ | | | | Common | | | | | (concentrator) | | | | +----------------+ | | | | | | v v v v +---------------------------------------+ | Core DB (API) | +---------------------------------------+ | v +---------------------------------------+ | Aristo DB (driver,concentrator) | +---------------------------------------+ | | v v +--------------+ +---------------------+ | Kvt (driver) | | Aristo MPT (driver) | +--------------+ +---------------------+ | | v v +---------------------------------------+ | Rocks DB (engine) | +---------------------------------------+
Here is a list of path references for the components with some explanation. The sources for the components are not always complete but indicate the main locations where to start looking at.
-
-
Sources:
./nimbus/db/core_db/backend/aristo_* -
Synopsis:
Combines both, the Kvt and the Aristo driver sub-modules providing an interface similar to the legacy DB (concentrator) module.
-
-
-
Sources:
./nimbus/db/aristo* -
Synopsis:
Revamped implementation of a hexary Merkle Patricia Tree.
-
-
-
Sources:
./nimbus/common* -
Synopsis:
Collected information for running block chain execution layer applications.
-
-
-
Sources:
./nimbus/db/core_db* -
Synopsis:
Database abstraction layer. Unless for legacy applications, there should be no need to reach out to the layers below.
-
-
-
Sources:
./nimbus/core/executor/* ./nimbus/evm/* -
Synopsis:
An implementation of the Ethereum Virtual Machine.
-
-
-
Sources:
./vendor/nim-eth/eth/trie/hexary.nim -
Synopsis:
Implementation of an MPT, see compact Merkle Patricia Tree.
-
-
-
Sources:
./vendor/nim-eth/eth/trie/db.nim -
Synopsis:
Key value table interface to be used directly for key-value storage or by the Hexary DB (driver) module for storage. Some magic is applied in order to treat hexary data accordingly (based on key length.)
-
-
-
Sources:
./nimbus/db/kvt* -
Synopsis:
Key value table interface for the Aristo DB (driver) module. Contrary to the Key-value table (driver), it is not used for MPT data.
-
-
-
Sources:
./nimbus/db/ledger* -
Synopsis:
Abstraction layer for either the legacy cache (driver) accounts cache (which works with the legacy DB (driver) backend only) or the ledger cache (driver) re-write which is supposed to work with all Core DB (API) backends.
-
-
-
Sources:
./nimbus/db/ledger/accounts_ledger.nim
./nimbus/db/ledger/backend/accounts_ledger*
./nimbus/db/ledger/distinct_ledgers.nim -
Synopsis:
Management of accounts and storage data. This is a re-write of the legacy DB (driver) which is supposed to work with all Core DB (API) backends.
-
-
-
Sources:
./nimbus/db/core_db/backend/legacy_* -
Synopsis:
Legacy database abstraction. It mostly forwards requests directly to the to the Key-value table (driver) and/or the hexary DB (driver).
-
-
-
Sources:
./vendor/nim-rocksdb/* -
Synopsis:
Persistent storage engine.
-
-
-
Sources:
./nimbus/evm/state.nim
./nimbus/evm/types.nim -
Synopsis:
Integrated collection of modules and methods relevant for the EVM.
-